Assessment and prediction of shoreline change using multi-temporal satellite data and geostatistics: A case study on the eastern coast of India. Issue 3 (7th February 2022)

• Record Type: Journal Article
• Authors: Basheer Ahammed, K. K.; Pandey, Arvind Chandra
• Is Part Of: Journal of water and climate change. Volume 13:Issue 3(2022)
• Page Start: 1477
• Page End: 1493
• Publication Date: 2022-02-07
• Subjects: Andhra Pradesh -- DSAS -- future prediction -- GIS -- shoreline change; Water -- Periodicals; Hydrology -- Periodicals; Climatic changes -- Periodicals; Climatic changes; Hydrology; Water; Electronic journals; Periodicals; 333.9116
• DOI: 10.2166/wcc.2022.270
• Languages: English
• ISSNs: 2040-2244

Abstract

Abstract: Climate change and rising sea level is transforming global coastlines as corroborated by significant changes in the position of shoreline witnessed through coastal erosion or accretion. Andhra Pradesh has the second longest (972 km) coastline in India. The present study analyzed shoreline change and its future prediction by employing satellite-derived data and geographic information system. End point rate (EPR) and linear regression rate (LRR) statistical tools in the Digital Shoreline Analysis System (DSAS) were used to estimate historical shoreline change rate between 1973 and 2015. Erosion and accretion of the coastline were delineated from Landsat satellite images for 1973, 1980, 1990, 2000, 2010, and 2015; subsequently, shoreline is predicted for short-term (2025) and long-term (2050) periods. The study showcased that the river mouths of Krishna and Godavari experienced higher rate of change in shoreline position influenced by the deltaic environment and fluvial processes. LRR model prediction depicts the average rate of shoreline change during 2015–2025 will be −4.64 m, while between 2015 and 2050 it will increase to −16.25 m. The study observed that the error between predicted and actual shoreline is higher in the river mouth and deltaic plains. Predicted shoreline position will provide baseline information for adaptation strategies and policy framework for coastal management. HIGHLIGHTS: Report about the coastal erosion, and its future prediction. Remote sensing data were used for the monitoring of the coastline. The geospatial technology and statistical change measurement techniques were used. The results highlighted the impacts on coast with erosion and accretion along the shoreline.